As AI grows, so does the infinite number of uses for its application, and the financial industry, in particular, stands to benefit from its adoption. While AI is already being used for applications such as fraud prevention, credit management, trade analysis, personalized banking, and risk management, a big opportunity for its use lies in the management of data.
Today we live in a world of massive amounts of data. Unstructured data, in particular is rife online, and being produced at incomprehensible rates. Anything from a tweet, to a social media post, to raw data from reports is considered unstructured data. In fact, over 80% of all data created is unstructured in its format. Alongside this, less than 1% of unstructured data is used or analyzed in any way.
This presents an issue for financial institutions who need to process very large amounts of data to make important decisions or undertake action in their daily business. With all the unstructured data that is present online, it is very difficult to determine the value of information being shared, while also inferring its relevance in an actionable context.
With AI and machine learning, there is the potential for this data to be processed quickly and effectively so that financial companies can deduce what is needed from all the information out there. The potential of this is enormous for data hungry financial institutions who previously would attempt to process unstructured data through employing countless man-hours to sift through the information, distill meaning, and convert it into function.
Decision making can be accelerated with the use of AI to process data for financial institutions, which is the key reason for its increased adoption. Excitingly, AI has the ability to scan through copious amounts of data and derive not just important insights, but also analyze the sentiment of whatever it is processing.
The ability to surmise information, pull out the important market insights, and capture the tone and sentiment of data will provide an invaluable edge to financial companies that utilize AI and machine learning to sift through the previously impossible mountain of unstructured data that passes through their virtual doors.